Detection and Segmentation of Multiple Touching Product

X-ray images of pistachio nuts on conveyor trays for product inspection are considered. The rst step in such a processor is to locate each individual item and place it in a separate le for input to a classiier to determine the quality of each nut. This paper considers new techniques to: detect each item (each nut can be in any orientation, we employ new rotation-invariant lters to locate each item independent of its orientation), produce separate image les for each item (a new blob coloring algorithm provides this for isolated (non-touching) input items), segmentation to provide separate image les for touching or overlapping input items (we use a morphological watershed transform to achieve this), and morphological processing to remove the shell and produce an image of only the nutmeat. Each of these operations and algorithms are detailed and quantitative data for each are presented for the X-ray image nut inspection problem noted. These techniques are of general use in many diierent product inspection problems in agriculture and other areas.